Primary Dependent Variables
- Primary dependent/outcome variable
- Secondary outcome variables:
- A
- B
XXX from the XXX Research Team is looking to engage in consultation with the Telethon Kids Institute’s Biometrics team to undertake statistical analysis to determine brief project summary.
Project roles:
Study overview to put the analysis in context.
The following data files were provided by XXX:
file.xlsx (DD MMM YYYY)file.sav (DD MMM YYYY)
Statistical models will be prepared for the dependant measures identified above with some commentary regarding their interpretation and statistical significance in terms of 95% confidence intervals. Where appropriate, figures will be prepared to help convey the analysis findings. Descriptive statistics can also be provided in the final result/manuscript preparation upon request.
Commentary around the methods and results of model creation will be provided in the form of a report that will include “copy-and-paste” paragraphs for manuscript preparation and a more detailed analysis summary. The analysis and reporting will be completed in the R programming language and all R script files associated with the analysis will be made available to the researcher upon request.
Assuming the data are tidy and clean, we estimate 4-6 days of analysis time (@$850 exc GST p/d), which does not include final result preparation time. Up to two Biometrics Biostatisticians to be included as authors on resulting publication(s) (assuming sufficient academic contributions are made).
It would be worthwhile preparing a skeleton of the tables for the paper to make the most efficient use of the analysis time, as working through multiple iterations of possible tables (which we are happy to do if required) will increase the analysis time/cost.
Final table prep and contribution to paper writing, within reason, is provided in-kind. Cost recovery for this function will be necessary if there are substantial edits/revisions/changes-of-mind.
This document was prepared using the software R, via the RStudio IDE, and was written in RMarkdown.
## R version 3.5.3 (2019-03-11)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 8.1 x64 (build 9600)
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## Matrix products: default
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## locale:
## [1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252
## [3] LC_MONETARY=English_Australia.1252 LC_NUMERIC=C
## [5] LC_TIME=English_Australia.1252
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
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## other attached packages:
## [1] captioner_2.2.3 GGally_1.4.0 broom_0.5.1
## [4] kableExtra_1.0.0 knitr_1.21 biometrics_1.0.3
## [7] ProjectTemplate_0.8.2 lubridate_1.7.4 forcats_0.3.0
## [10] stringr_1.3.1 dplyr_0.8.0.1 purrr_0.2.5
## [13] readr_1.3.1 tidyr_0.8.2 tibble_2.0.1
## [16] ggplot2_3.1.0 tidyverse_1.2.1 repmis_0.5
##
## loaded via a namespace (and not attached):
## [1] tidyselect_0.2.5 xfun_0.4 reshape2_1.4.3
## [4] haven_2.0.0 lattice_0.20-38 colorspace_1.4-0
## [7] generics_0.0.2 viridisLite_0.3.0 htmltools_0.3.6
## [10] yaml_2.2.0 rlang_0.3.1 R.oo_1.22.0
## [13] pillar_1.3.1 glue_1.3.0 withr_2.1.2
## [16] R.utils_2.7.0 RColorBrewer_1.1-2 modelr_0.1.2
## [19] readxl_1.2.0 R.cache_0.13.0 plyr_1.8.4
## [22] munsell_0.5.0 gtable_0.2.0 cellranger_1.1.0
## [25] rvest_0.3.2 R.methodsS3_1.7.1 evaluate_0.12
## [28] labeling_0.3 Rcpp_1.0.0 backports_1.1.3
## [31] scales_1.0.0 webshot_0.5.1 jsonlite_1.6
## [34] hms_0.4.2 digest_0.6.18 stringi_1.3.1
## [37] grid_3.5.3 cli_1.0.1 tools_3.5.3
## [40] magrittr_1.5 lazyeval_0.2.1 crayon_1.3.4
## [43] pkgconfig_2.0.2 data.table_1.12.0 xml2_1.2.0
## [46] reshape_0.8.8 assertthat_0.2.0 rmarkdown_1.11
## [49] httr_1.4.0 rstudioapi_0.9.0 R6_2.3.0
## [52] igraph_1.2.2 nlme_3.1-137 compiler_3.5.3